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State Abstraction
Compressing the full robot and environment state into a compact representation that preserves information relevant to the task while discarding irrelevant details. State abstraction reduces the dimensionality of the learning problem and improves generalization. Learned state abstractions (from autoencoders or contrastive methods) are preferred over hand-crafted ones.